1. Field of the Invention
The present invention relates to a wireless communication apparatus, a wireless communication method, and a computer program whereby data is communicated with increased transmission capacity by means of a spatial multiplexing (MIMO) communication technique using paired transmitters having a plurality of antennas each. More particularly, the present invention relates to a wireless communication apparatus, a wireless communication method, and a computer program whereby spatially multiplexed communication is conducted by compensating for phase and amplitude imbalances existing among transmit and receive branches, and thereby obtaining a suitable channel matrix.
2. Description of the Related Art
Wireless networks are now the subject of much attention, being systems free from the wiring involved in wired communication methods of the past. Specifications such as IEEE 802.11 (Institute of Electrical and Electronics Engineers 802.11) and IEEE 802.15 are recognized standards for wireless networks. For example, in IEEE 802.11a/g, a type of multi-carrier modulation method known as orthogonal frequency division multiplexing (OFDM) is implemented as the standard wireless LAN specification.
In addition, although the IEEE 802.11a/g standard supports modulation methods that can achieve a maximum data transfer rate of 54 Mbps, there is demand for a next-generation wireless LAN standard able to realize even greater bit rates. Multi-Input Multi-Output, or MIMO, is receiving attention as one technology for realizing faster wireless communication, and a MIMO-OFDM communication method has been adopted in IEEE 802.11n, an amendment to the IEEE 802.11 standard.
MIMO is a communication method that realizes a spatially multiplexed stream by providing a plurality of antenna elements at both the transmitter and the receiver. On the transmit side, a plurality of transmit data is multiplexed by performing space-time coding, distributed across a plurality of transmit antennas, and then transmitted on a channel. Likewise, on the receive side, a receive signal received by a plurality of receive antennas via the channel is separated into the plurality of transmit data by performing space-time decoding. Thus, the original data can be obtained without inter-stream cross-talk. By means of a MIMO communication method, the transmission capacity can be increased in accordance with the number of antennas, and without increasing the frequency band. As a result, an improved data transfer rate can be achieved. Furthermore, since spatial multiplexing is used, frequency utilization efficiency is also favorable. MIMO is a communication method that takes advantage of channel characteristics, and is thus different from a simple adaptive array.
In MIMO communication, a channel matrix H is used to respectively calculate a transmit weight matrix and a receive weight matrix, for example. The transmit weight matrix is used to spatially multiplex a transmit stream from a plurality of transmit branches on the transmit side. The receive weight matrix is used to spatially separate a spatially multiplexed signal into a plurality of streams at the receive side. The channel matrix H is a numeric matrix whose elements are channel information corresponding to transmit and receive antenna pairs. The channel information referred to herein is made up of transfer coefficients having phase and amplitude components. Normally, the channel matrix can be estimated by carrying out a frame exchange sequence containing a training sequence made up of pre-defined reference symbols for exciting the channel matrix between the transmitter and receiver.
It has been established that by setting the channel matrix H equal to the singular value decomposition (SVD) UDVH (in other words, by taking H=UDVH), the transmit beamforming matrix V and the receive weight matrix UH are obtained. For example, proposals have been regarding a wireless communication system wherein the quantity of feedback information sent from the receive side to the transmit side is compressed. Instead of feeding back the transmit beamforming matrix V obtained by taking the SVD of channel information matrix acquired at the receive side, packets containing the training sequence are transmitted from the receive side to the transmit side, and the transmit beamforming matrix V is thus also obtained by SVD on the transmit side (see Japanese Unexamined Patent Application Publication No. 2005-160030, paragraph 0045, for example).
Meanwhile, in multi-antenna communication using a plurality of transmit and receive antennas (as typified by MIMO and adaptive arrays), there exist imbalances in the transfer coefficients (i.e., the phase and amplitude) among the transmit and receive branches. In the digital processor on the receive side, the combination of the spatial transfer coefficients and the transfer coefficients in the analog unit within the apparatus are recognized as channels, and thus branch imbalances in the analog unit can lead to channel misrecognition. For this reason, in order to obtain an accurate channel matrix and realize optimal beamforming, the training sequence used for channel estimation that is exchanged between the transmitter and receiver is multiplied by calibration coefficients to correct phase and amplitude imbalances.
For example, proposals have been made regarding a wireless communication system that conducts the following. Calibration coefficients are first found for each antenna at both the transmitter and receiver. Then, when feeding back the reference signal feedback and solving for the transfer coefficients on the basis of the reference signal, the system is calibrated using the calibration coefficients for the receive antennas as well as the calibration coefficients for the transmit antennas, respectively. As a result of such calibration, mismatches in the channel information matrix in the forward and reverse directions are corrected (see Japanese Unexamined Patent Application Publication No. 2005-160030, paragraph 0052, for example).
It is also thought that antenna calibration should be conducted at the receiver rather than the transmitter. This is because the calibration coefficients are based on branches with large output in order to accommodate the transmit spectral mask when the transmit signal is multiplied by calibration correction coefficients and transmitted. If there are large fluctuations in the gain in each transmit branch, then the power loss accompanying the multiplication by the calibration coefficients also becomes large, resulting in degradation in the characteristics of RF circuit chips, where fluctuations are small.
Consequently, when a MIMO communication device receives a frame containing a training sequence for exciting the channel matrix, training sequence portions in respective receive branches are respectively multiplied by calibration coefficients to correct phase and amplitude imbalances.
Meanwhile, on the receive side of the wireless communication, the noise contained in the receive signal (i.e., the signal-to-noise ratio, or SNR) is estimated. The SNR is estimated in order to conduct efficient transmission by switching to more suitable modulation and coding methods or data transfer rates on the basis of communication quality, as represented by quantities such as the estimated SNR. In addition, soft decision decoding techniques estimate the receive bit sequence by conducting maximum likelihood sequence estimation using deinterleave processing and Viterbi decoding. With such soft decision decoding techniques, some kind of likelihood information is provided to the decoder, with the likelihood information being solved for on the basis of the noise power. For this reason, there is concern that decoding performance will degrade if the noise estimation is poor.
However, when respectively multiplying the receive signals in each receive branch by calibration coefficients in order to compensate for phase and amplitude imbalances existing among transmit and receive branches as described above, the above corresponds to invalid gain being applied among branches. For this reason, in a system that conducts antenna calibration on the receive side, the occurrence of errors in the estimation of the SNR and the likelihood information performed when calibrating is dependent on the noise estimation method, leading to concerns regarding the degradation of reception characteristics.